Add to ORKGIdentification of outliers can lead to the discovery of unexpected, interesting, and implicit knowledge. Existing methods are designed for detecting spatial outliers in multidimensional geometric data sets, where a distance metric is available. In this paper, we focus on detecting spatial outliers in graph structured data sets. We define tests for spatial outliers in graph structured data sets, analyze the statistical foundation underlying our approach, design a fast algorithm to detect spatial outliers, provide the cost model for outlier detection procedures. In addition, we provide experimental results from the application of our algorithm on a Minneapolis-St. Paul(Twin-Cities) traffic dataset to show its effectiveness and usefulness
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach...
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach...
The detection of spatial outliers helps extract important and valuable information from large spatia...
© 2019 IEEE. Outlier detection, or the identification of observations that differ significantly from...
© 2019 IEEE. Outlier detection, or the identification of observations that differ significantly from...
Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we ...
Outlier detection, as a data mining task, is to identify a small set of data that is considerably di...
Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we ...
Abstract: Outlier detection concerns discovering some unusual data whose behavior is exceptional com...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
Distance-based outlier detection is widely adopted in many fields, e.g., data mining and machine lea...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
Outlier detection techniques in spatial data should allow to identify two types of outliers: global...
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach...
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach...
The detection of spatial outliers helps extract important and valuable information from large spatia...
© 2019 IEEE. Outlier detection, or the identification of observations that differ significantly from...
© 2019 IEEE. Outlier detection, or the identification of observations that differ significantly from...
Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we ...
Outlier detection, as a data mining task, is to identify a small set of data that is considerably di...
Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we ...
Abstract: Outlier detection concerns discovering some unusual data whose behavior is exceptional com...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
Distance-based outlier detection is widely adopted in many fields, e.g., data mining and machine lea...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
Outlier detection techniques in spatial data should allow to identify two types of outliers: global...
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach...
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach...
The detection of spatial outliers helps extract important and valuable information from large spatia...